欢迎大家投稿Electronics ：Special Issue "Machine Learning in Music/Audio Signal Processing"，Deadline for manuscript submissions: 20 May 2023。

网址：https://www.mdpi.com/journal/electronics/special_issues/4NFI1LYG93


Electronics

Electronicsis an international,peer-reviewed, open access journal on the science of electronics and its applications published semimonthly online by MDPI.


Special Issue Editors


Dr. Jing Wang

Guest Editor

School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
Interests:speech/audio signal processing; multimedia communications; virtual reality
E-Mail: wangjing@bit.edu.cn
Website


Prof. Dr. Maoshen Jia

Guest Editor

Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China

Interests:multichannel audio signal processing; audio coding and array signal processing

E-Mail: jiamaoshen@bjut.edu.cn

Website


Special Issue Information

With the development of machine learning technology, especially deep learning and neural networks, the performance of music and audio signal processing has been improved largely in the fields of audio information understanding, extracting, generation and recovery. More efficient audio signal processing and analysis techniques based on data-driven approaches are needed in order to make it possible for humans to experience better speech- and music-related products. Machine learning methods cover the research of supervised, unsupervised, semi-supervised and reinforcement learning, which can be applied to solve prediction and classification problems in music/audio signal processing. Compared with machine learning in speech signal processing, it is more difficult to analyze and process audio, especially music, as it is more complex in signal characteristics and it is not easy to construct a large number of datasets. This kind of problem brings new challenges to the research of machine learning techniques in music/audio signal processing. There is still the potential to combine machine learning with traditional signal processing methods when facing complex music and audio. In the future, not only will machine learning make music and audio more convenient for the user experience, but high-level artificial intelligent methods will also lead to more applications in intelligent hardware, smart education, internet music, entertainment, AI composition and even broader metaverse audio scenarios.
This Special Issue mainly aims to show better solutions regarding machine learning techniques in music and audio signal processing, such as music information retrieval, audio classification, speech/music enhancement and music/sound synthesis, as well as the general audio computational auditory scene analysis. Topics of interest include, but are not limited to, the following:
  • General data-driven methods in music and audio signal analysis and processing;
  • Machine learning methods for music/audio information retrieval such as music instrument classification, mood classification, music melody extraction, etc.;
  • Approaches for audio scene analysis including audio tagging, audio classification, sound event detection and the related signal processing in the generalized acoustic scene;
  • Deep learning methods for speech and audio processing such as speech/music enhancement, speech/audio bandwidth extension, speech/music separation and music/sound synthesis;
  • Necessary techniques for machine learning-based music/audio signal processing such as database collection, emotion analysis, sound visualization, music evaluation, etc.


Manuscript Submission Information
Manuscripts should be submitted online atwww.mdpi.combyregisteringandlogging in to this website. Once you are registered.Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on theInstructions for Authorspage.Electronicsis an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit theInstructions for Authorspage before submitting a manuscript. TheArticle Processing Charge (APC)for publication in thisopen accessjournal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI'sEnglish editing serviceprior to publication or during author revisions.


Keywords

  • machine learning

  • deep learning

  • neural networks

  • audio signal processing

  • music information retrieval

  • audio scene analysis


Published Papers

This special issue is now open for submission.